Op-pymize.upn is a workshop-guide focused on solving problems in an optimal way, obtaining the best results through the Python programming language. It is divided into two sections, the introductory page and the problems, initially the content referring to the optimization topic and the code that will solve the exercises on the next page will be observed. The second part includes two types of exercises according to their application, these are shown in such a way that the student will be completing fields as he advances through the explanation and solution of the problem, which allows him to carry out various cognitive processes in real time.
The OER could be very useful in several subjects of the computational science curriculum since it contains different topics of linear algebra and optimization, but it also manages to break down others such as differential calculus and programming, allowing interaction and mutual learning, denoting the importance of find the relationships that exist between different areas of knowledge.
Mainly, it is a resource that allows the teacher to strengthen several of their digital skills (Creation of digital content, Teacher professional development and Lifelong Learning ...) when using it, learning how to use it, how to interact with students and how to achieve learning supplying the presence. It allows you to gain insight into how feasible and effective it can be to create and use this type of content in your classroom. In addition, it is interesting and attractive to implement as a reinforcement or practical exercise within your class, where it is not only limited to certain topics, but can go further, thus generating other perspectives and interactions through the connections that exist. between different topics and how they can be complemented to respond to a problem or understand other areas.
On the other hand, students would be interacting in a medium that they know and use daily, with the exception that they would be taking advantage of it to strengthen concepts and learn to solve real optimization problems through the Python programming language. We also provide them with an interactive, dynamic and proactive environment that attracts and encourages them to delve a little deeper into the main topic proposed by the OER in conjunction with the other items it includes. The environment has been created so that the student does not feel overwhelmed but awakens in him an interest and his own taste for solving optimization problems through programming, providing him with knowledge so that he is later able to analyze, think and solve in detail any exercise, contemplating all its peculiarities and possibilities.
COMPSAC OER COMPETITION
